Overview

Brought to you by YData

Dataset statistics

Number of variables20
Number of observations6061
Missing cells10089
Missing cells (%)8.3%
Duplicate rows4
Duplicate rows (%)0.1%
Total size in memory7.0 MiB
Average record size in memory1.2 KiB

Variable types

Text3
Numeric6
Categorical8
Unsupported2
DateTime1

Alerts

Dataset has 4 (0.1%) duplicate rowsDuplicates
state is highly imbalanced (53.3%)Imbalance
door is highly imbalanced (85.8%)Imbalance
volume has 370 (6.1%) missing valuesMissing
tip_dvigatelja has 217 (3.6%) missing valuesMissing
body has 675 (11.1%) missing valuesMissing
state has 533 (8.8%) missing valuesMissing
door has 752 (12.4%) missing valuesMissing
fuel has 519 (8.6%) missing valuesMissing
transmission has 378 (6.2%) missing valuesMissing
conditioner has 1006 (16.6%) missing valuesMissing
audio has 1575 (26.0%) missing valuesMissing
mileage has 1145 (18.9%) missing valuesMissing
mileage_orig has 2919 (48.2%) missing valuesMissing
fone is an unsupported type, check if it needs cleaning or further analysisUnsupported
manth is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2025-02-27 17:21:24.159005
Analysis finished2025-02-27 17:21:30.087266
Duration5.93 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

brend
Text

Distinct61
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size426.8 KiB
2025-02-27T20:21:30.273275image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length6.6856954
Min length3

Characters and Unicode

Total characters40522
Distinct characters56
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.2%

Sample

1st rowToyota
2nd rowVolkswagen
3rd rowToyota
4th rowBMW
5th rowLexus
ValueCountFrequency (%)
toyota 911
15.0%
volkswagen 843
13.9%
mercedes-benz 580
 
9.6%
lexus 497
 
8.2%
bmw 432
 
7.1%
ford 328
 
5.4%
audi 301
 
5.0%
opel 248
 
4.1%
nissan 217
 
3.6%
honda 194
 
3.2%
Other values (51) 1510
24.9%
2025-02-27T20:21:30.624605image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4533
 
11.2%
o 3653
 
9.0%
a 3133
 
7.7%
s 2827
 
7.0%
n 2330
 
5.7%
d 1824
 
4.5%
i 1547
 
3.8%
l 1508
 
3.7%
t 1447
 
3.6%
M 1372
 
3.4%
Other values (46) 16348
40.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32150
79.3%
Uppercase Letter 7792
 
19.2%
Dash Punctuation 580
 
1.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 1372
17.6%
B 1014
13.0%
T 1002
12.9%
V 916
11.8%
L 551
7.1%
W 432
 
5.5%
A 366
 
4.7%
F 348
 
4.5%
H 343
 
4.4%
O 248
 
3.2%
Other values (19) 1200
15.4%
Lowercase Letter
ValueCountFrequency (%)
e 4533
14.1%
o 3653
11.4%
a 3133
 
9.7%
s 2827
 
8.8%
n 2330
 
7.2%
d 1824
 
5.7%
i 1547
 
4.8%
l 1508
 
4.7%
t 1447
 
4.5%
u 1343
 
4.2%
Other values (16) 8005
24.9%
Dash Punctuation
ValueCountFrequency (%)
- 580
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 39720
98.0%
Common 580
 
1.4%
Cyrillic 222
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4533
 
11.4%
o 3653
 
9.2%
a 3133
 
7.9%
s 2827
 
7.1%
n 2330
 
5.9%
d 1824
 
4.6%
i 1547
 
3.9%
l 1508
 
3.8%
t 1447
 
3.6%
M 1372
 
3.5%
Other values (35) 15546
39.1%
Cyrillic
ValueCountFrequency (%)
З 74
33.3%
А 72
32.4%
В 50
22.5%
Г 17
 
7.7%
У 4
 
1.8%
И 1
 
0.5%
Л 1
 
0.5%
М 1
 
0.5%
а 1
 
0.5%
з 1
 
0.5%
Common
ValueCountFrequency (%)
- 580
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40300
99.5%
Cyrillic 222
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4533
 
11.2%
o 3653
 
9.1%
a 3133
 
7.8%
s 2827
 
7.0%
n 2330
 
5.8%
d 1824
 
4.5%
i 1547
 
3.8%
l 1508
 
3.7%
t 1447
 
3.6%
M 1372
 
3.4%
Other values (36) 16126
40.0%
Cyrillic
ValueCountFrequency (%)
З 74
33.3%
А 72
32.4%
В 50
22.5%
Г 17
 
7.7%
У 4
 
1.8%
И 1
 
0.5%
Л 1
 
0.5%
М 1
 
0.5%
а 1
 
0.5%
з 1
 
0.5%

volume
Real number (ℝ)

MISSING 

Distinct234
Distinct (%)4.1%
Missing370
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean2259.8559
Minimum1000
Maximum7600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.7 KiB
2025-02-27T20:21:30.763656image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1400
Q11800
median2000
Q32500
95-th percentile3500
Maximum7600
Range6600
Interquartile range (IQR)700

Descriptive statistics

Standard deviation704.72919
Coefficient of variation (CV)0.31184696
Kurtosis3.646301
Mean2259.8559
Median Absolute Deviation (MAD)400
Skewness1.4527588
Sum12860840
Variance496643.23
MonotonicityNot monotonic
2025-02-27T20:21:30.913690image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 1296
21.4%
1800 444
 
7.3%
2500 443
 
7.3%
2200 362
 
6.0%
3000 343
 
5.7%
1600 329
 
5.4%
3500 327
 
5.4%
1900 239
 
3.9%
2400 226
 
3.7%
1500 201
 
3.3%
Other values (224) 1481
24.4%
(Missing) 370
 
6.1%
ValueCountFrequency (%)
1000 79
1.3%
1098 1
 
< 0.1%
1100 6
 
0.1%
1198 1
 
< 0.1%
1200 20
 
0.3%
1230 1
 
< 0.1%
1246 2
 
< 0.1%
1250 1
 
< 0.1%
1300 47
0.8%
1323 1
 
< 0.1%
ValueCountFrequency (%)
7600 1
 
< 0.1%
6100 1
 
< 0.1%
6000 3
 
< 0.1%
5900 1
 
< 0.1%
5700 14
0.2%
5600 3
 
< 0.1%
5599 1
 
< 0.1%
5500 4
 
0.1%
5496 1
 
< 0.1%
5400 3
 
< 0.1%

tip_dvigatelja
Categorical

MISSING 

Distinct5
Distinct (%)0.1%
Missing217
Missing (%)3.6%
Memory size690.0 KiB
Дизель
2132 
Бензин
1424 
Бензин-Газ
1225 
Гибрид
944 
Электро
 
119

Length

Max length10
Median length6
Mean length6.8588296
Min length6

Characters and Unicode

Total characters40083
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowДизель
2nd rowБензин-Газ
3rd rowГибрид
4th rowБензин
5th rowБензин

Common Values

ValueCountFrequency (%)
Дизель 2132
35.2%
Бензин 1424
23.5%
Бензин-Газ 1225
20.2%
Гибрид 944
15.6%
Электро 119
 
2.0%
(Missing) 217
 
3.6%

Length

2025-02-27T20:21:31.068726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-27T20:21:31.211633image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
дизель 2132
36.5%
бензин 1424
24.4%
бензин-газ 1225
21.0%
гибрид 944
16.2%
электро 119
 
2.0%

Most occurring characters

ValueCountFrequency (%)
и 6669
16.6%
з 6006
15.0%
н 5298
13.2%
е 4900
12.2%
Б 2649
 
6.6%
л 2251
 
5.6%
Г 2169
 
5.4%
Д 2132
 
5.3%
ь 2132
 
5.3%
- 1225
 
3.1%
Other values (8) 4652
11.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31789
79.3%
Uppercase Letter 7069
 
17.6%
Dash Punctuation 1225
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
и 6669
21.0%
з 6006
18.9%
н 5298
16.7%
е 4900
15.4%
л 2251
 
7.1%
ь 2132
 
6.7%
а 1225
 
3.9%
р 1063
 
3.3%
б 944
 
3.0%
д 944
 
3.0%
Other values (3) 357
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
Б 2649
37.5%
Г 2169
30.7%
Д 2132
30.2%
Э 119
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1225
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 38858
96.9%
Common 1225
 
3.1%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
и 6669
17.2%
з 6006
15.5%
н 5298
13.6%
е 4900
12.6%
Б 2649
 
6.8%
л 2251
 
5.8%
Г 2169
 
5.6%
Д 2132
 
5.5%
ь 2132
 
5.5%
а 1225
 
3.2%
Other values (7) 3427
8.8%
Common
ValueCountFrequency (%)
- 1225
100.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 38858
96.9%
ASCII 1225
 
3.1%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
и 6669
17.2%
з 6006
15.5%
н 5298
13.6%
е 4900
12.6%
Б 2649
 
6.8%
л 2251
 
5.8%
Г 2169
 
5.6%
Д 2132
 
5.5%
ь 2132
 
5.5%
а 1225
 
3.2%
Other values (7) 3427
8.8%
ASCII
ValueCountFrequency (%)
- 1225
100.0%

god
Real number (ℝ)

Distinct47
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2005.5722
Minimum1958
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.7 KiB
2025-02-27T20:21:31.348647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1958
5-th percentile1992
Q12001
median2006
Q32012
95-th percentile2017
Maximum2019
Range61
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.4775756
Coefficient of variation (CV)0.0037284001
Kurtosis0.11985471
Mean2005.5722
Median Absolute Deviation (MAD)5
Skewness-0.40338227
Sum12155773
Variance55.914137
MonotonicityNot monotonic
2025-02-27T20:21:31.499681image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
2006 391
 
6.5%
2005 357
 
5.9%
2007 348
 
5.7%
2013 339
 
5.6%
2008 334
 
5.5%
2004 322
 
5.3%
2003 295
 
4.9%
2000 254
 
4.2%
2014 250
 
4.1%
2001 244
 
4.0%
Other values (37) 2927
48.3%
ValueCountFrequency (%)
1958 1
 
< 0.1%
1967 1
 
< 0.1%
1973 1
 
< 0.1%
1975 1
 
< 0.1%
1977 1
 
< 0.1%
1978 1
 
< 0.1%
1979 2
 
< 0.1%
1980 7
0.1%
1981 1
 
< 0.1%
1982 2
 
< 0.1%
ValueCountFrequency (%)
2019 102
 
1.7%
2018 152
2.5%
2017 151
2.5%
2016 159
2.6%
2015 173
2.9%
2014 250
4.1%
2013 339
5.6%
2012 225
3.7%
2011 167
2.8%
2010 182
3.0%

prise
Real number (ℝ)

Distinct602
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7485.5941
Minimum1000
Maximum55000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.7 KiB
2025-02-27T20:21:31.651715image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1330
Q12700
median5300
Q310000
95-th percentile20000
Maximum55000
Range54000
Interquartile range (IQR)7300

Descriptive statistics

Standard deviation6482.9722
Coefficient of variation (CV)0.86605981
Kurtosis4.3019798
Mean7485.5941
Median Absolute Deviation (MAD)3200
Skewness1.8088854
Sum45370186
Variance42028929
MonotonicityNot monotonic
2025-02-27T20:21:31.806026image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 139
 
2.3%
2500 135
 
2.2%
3500 133
 
2.2%
4500 114
 
1.9%
1500 105
 
1.7%
3000 94
 
1.6%
1700 88
 
1.5%
5000 87
 
1.4%
2700 85
 
1.4%
1000 83
 
1.4%
Other values (592) 4998
82.5%
ValueCountFrequency (%)
1000 83
1.4%
1001 1
 
< 0.1%
1050 3
 
< 0.1%
1100 49
0.8%
1111 9
 
0.1%
1150 14
 
0.2%
1199 1
 
< 0.1%
1200 77
1.3%
1234 1
 
< 0.1%
1250 26
 
0.4%
ValueCountFrequency (%)
55000 2
< 0.1%
44750 1
< 0.1%
42500 1
< 0.1%
42000 2
< 0.1%
40000 1
< 0.1%
39900 1
< 0.1%
39805 1
< 0.1%
38950 2
< 0.1%
37900 1
< 0.1%
37500 2
< 0.1%

body
Categorical

MISSING 

Distinct14
Distinct (%)0.3%
Missing675
Missing (%)11.1%
Memory size681.5 KiB
седан
1827 
универсал
925 
внедорожник
703 
хетчбек
660 
минивен
608 
Other values (9)
663 

Length

Max length12
Median length11
Mean length7.3847011
Min length4

Characters and Unicode

Total characters39774
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowуниверсал
2nd rowминивен
3rd rowхетчбек
4th rowвнедорожник
5th rowхетчбек

Common Values

ValueCountFrequency (%)
седан 1827
30.1%
универсал 925
15.3%
внедорожник 703
 
11.6%
хетчбек 660
 
10.9%
минивен 608
 
10.0%
кроссовер 445
 
7.3%
микроавтобус 66
 
1.1%
купе 56
 
0.9%
лимузин 34
 
0.6%
фургон 23
 
0.4%
Other values (4) 39
 
0.6%
(Missing) 675
 
11.1%

Length

2025-02-27T20:21:31.963062image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
седан 1827
33.9%
универсал 925
17.2%
внедорожник 703
 
13.1%
хетчбек 660
 
12.3%
минивен 608
 
11.3%
кроссовер 445
 
8.3%
микроавтобус 66
 
1.2%
купе 56
 
1.0%
лимузин 34
 
0.6%
фургон 23
 
0.4%
Other values (4) 39
 
0.7%

Most occurring characters

ValueCountFrequency (%)
е 5897
14.8%
н 5431
13.7%
с 3716
9.3%
и 2994
7.5%
а 2842
7.1%
в 2770
7.0%
р 2635
6.6%
д 2530
 
6.4%
о 2502
 
6.3%
к 1946
 
4.9%
Other values (13) 6511
16.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39774
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
е 5897
14.8%
н 5431
13.7%
с 3716
9.3%
и 2994
7.5%
а 2842
7.1%
в 2770
7.0%
р 2635
6.6%
д 2530
 
6.4%
о 2502
 
6.3%
к 1946
 
4.9%
Other values (13) 6511
16.4%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 39774
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
е 5897
14.8%
н 5431
13.7%
с 3716
9.3%
и 2994
7.5%
а 2842
7.1%
в 2770
7.0%
р 2635
6.6%
д 2530
 
6.4%
о 2502
 
6.3%
к 1946
 
4.9%
Other values (13) 6511
16.4%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 39774
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
е 5897
14.8%
н 5431
13.7%
с 3716
9.3%
и 2994
7.5%
а 2842
7.1%
в 2770
7.0%
р 2635
6.6%
д 2530
 
6.4%
о 2502
 
6.3%
к 1946
 
4.9%
Other values (13) 6511
16.4%

state
Categorical

IMBALANCE  MISSING 

Distinct6
Distinct (%)0.1%
Missing533
Missing (%)8.8%
Memory size698.3 KiB
Отличное
3252 
Хорошее
2062 
Удовлетворительное
 
142
Новый
 
62
Битыйавто
 
9

Length

Max length18
Median length8
Mean length7.8514834
Min length5

Characters and Unicode

Total characters43403
Distinct characters22
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowОтличное
2nd rowОтличное
3rd rowОтличное
4th rowХорошее
5th rowОтличное

Common Values

ValueCountFrequency (%)
Отличное 3252
53.7%
Хорошее 2062
34.0%
Удовлетворительное 142
 
2.3%
Новый 62
 
1.0%
Битыйавто 9
 
0.1%
Плохое 1
 
< 0.1%
(Missing) 533
 
8.8%

Length

2025-02-27T20:21:32.107080image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-27T20:21:32.227106image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
отличное 3252
58.8%
хорошее 2062
37.3%
удовлетворительное 142
 
2.6%
новый 62
 
1.1%
битыйавто 9
 
0.2%
плохое 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
о 7875
18.1%
е 7803
18.0%
т 3554
8.2%
л 3537
8.1%
и 3403
7.8%
н 3394
7.8%
О 3252
7.5%
ч 3252
7.5%
р 2204
 
5.1%
Х 2062
 
4.8%
Other values (12) 3067
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37875
87.3%
Uppercase Letter 5528
 
12.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 7875
20.8%
е 7803
20.6%
т 3554
9.4%
л 3537
9.3%
и 3403
9.0%
н 3394
9.0%
ч 3252
8.6%
р 2204
 
5.8%
ш 2062
 
5.4%
в 355
 
0.9%
Other values (6) 436
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
О 3252
58.8%
Х 2062
37.3%
У 142
 
2.6%
Н 62
 
1.1%
Б 9
 
0.2%
П 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 43403
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 7875
18.1%
е 7803
18.0%
т 3554
8.2%
л 3537
8.1%
и 3403
7.8%
н 3394
7.8%
О 3252
7.5%
ч 3252
7.5%
р 2204
 
5.1%
Х 2062
 
4.8%
Other values (12) 3067
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 43403
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 7875
18.1%
е 7803
18.0%
т 3554
8.2%
л 3537
8.1%
и 3403
7.8%
н 3394
7.8%
О 3252
7.5%
ч 3252
7.5%
р 2204
 
5.1%
Х 2062
 
4.8%
Other values (12) 3067
 
7.1%

door
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)0.1%
Missing752
Missing (%)12.4%
Memory size405.4 KiB
4/5
5140 
2/3
 
138
6/7
 
31

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters15927
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4/5
2nd row4/5
3rd row4/5
4th row4/5
5th row4/5

Common Values

ValueCountFrequency (%)
4/5 5140
84.8%
2/3 138
 
2.3%
6/7 31
 
0.5%
(Missing) 752
 
12.4%

Length

2025-02-27T20:21:32.354134image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-27T20:21:32.455157image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
4/5 5140
96.8%
2/3 138
 
2.6%
6/7 31
 
0.6%

Most occurring characters

ValueCountFrequency (%)
/ 5309
33.3%
4 5140
32.3%
5 5140
32.3%
2 138
 
0.9%
3 138
 
0.9%
6 31
 
0.2%
7 31
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10618
66.7%
Other Punctuation 5309
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 5140
48.4%
5 5140
48.4%
2 138
 
1.3%
3 138
 
1.3%
6 31
 
0.3%
7 31
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 5309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15927
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 5309
33.3%
4 5140
32.3%
5 5140
32.3%
2 138
 
0.9%
3 138
 
0.9%
6 31
 
0.2%
7 31
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15927
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 5309
33.3%
4 5140
32.3%
5 5140
32.3%
2 138
 
0.9%
3 138
 
0.9%
6 31
 
0.2%
7 31
 
0.2%

fuel
Categorical

MISSING 

Distinct4
Distinct (%)0.1%
Missing519
Missing (%)8.6%
Memory size650.3 KiB
бензин
2465 
дизель
2083 
газ
799 
электро
 
195

Length

Max length7
Median length6
Mean length5.6026705
Min length3

Characters and Unicode

Total characters31050
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowдизель
2nd rowбензин
3rd rowбензин
4th rowдизель
5th rowбензин

Common Values

ValueCountFrequency (%)
бензин 2465
40.7%
дизель 2083
34.4%
газ 799
 
13.2%
электро 195
 
3.2%
(Missing) 519
 
8.6%

Length

2025-02-27T20:21:32.575184image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-27T20:21:32.692210image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
бензин 2465
44.5%
дизель 2083
37.6%
газ 799
 
14.4%
электро 195
 
3.5%

Most occurring characters

ValueCountFrequency (%)
з 5347
17.2%
н 4930
15.9%
е 4743
15.3%
и 4548
14.6%
б 2465
7.9%
л 2278
7.3%
д 2083
 
6.7%
ь 2083
 
6.7%
г 799
 
2.6%
а 799
 
2.6%
Other values (5) 975
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31050
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
з 5347
17.2%
н 4930
15.9%
е 4743
15.3%
и 4548
14.6%
б 2465
7.9%
л 2278
7.3%
д 2083
 
6.7%
ь 2083
 
6.7%
г 799
 
2.6%
а 799
 
2.6%
Other values (5) 975
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 31050
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
з 5347
17.2%
н 4930
15.9%
е 4743
15.3%
и 4548
14.6%
б 2465
7.9%
л 2278
7.3%
д 2083
 
6.7%
ь 2083
 
6.7%
г 799
 
2.6%
а 799
 
2.6%
Other values (5) 975
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 31050
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
з 5347
17.2%
н 4930
15.9%
е 4743
15.3%
и 4548
14.6%
б 2465
7.9%
л 2278
7.3%
д 2083
 
6.7%
ь 2083
 
6.7%
г 799
 
2.6%
а 799
 
2.6%
Other values (5) 975
 
3.1%

transmission
Categorical

MISSING 

Distinct6
Distinct (%)0.1%
Missing378
Missing (%)6.2%
Memory size742.7 KiB
автомат
2855 
5-тиступ.мех.
1985 
6-тиступ.мех.
747 
4-ёхступ.мех.
 
43
роботизированая
 
43

Length

Max length15
Median length7
Mean length9.9973605
Min length7

Characters and Unicode

Total characters56815
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6-тиступ.мех.
2nd row5-тиступ.мех.
3rd rowавтомат
4th row5-тиступ.мех.
5th rowавтомат

Common Values

ValueCountFrequency (%)
автомат 2855
47.1%
5-тиступ.мех. 1985
32.8%
6-тиступ.мех. 747
 
12.3%
4-ёхступ.мех. 43
 
0.7%
роботизированая 43
 
0.7%
полуавтомат 10
 
0.2%
(Missing) 378
 
6.2%

Length

2025-02-27T20:21:32.826242image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-27T20:21:32.953815image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
автомат 2855
50.2%
5-тиступ.мех 1985
34.9%
6-тиступ.мех 747
 
13.1%
4-ёхступ.мех 43
 
0.8%
роботизированая 43
 
0.8%
полуавтомат 10
 
0.2%

Most occurring characters

ValueCountFrequency (%)
т 11280
19.9%
а 5816
10.2%
м 5640
9.9%
. 5550
9.8%
о 3004
 
5.3%
в 2908
 
5.1%
и 2818
 
5.0%
х 2818
 
5.0%
у 2785
 
4.9%
п 2785
 
4.9%
Other values (13) 11411
20.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 45715
80.5%
Other Punctuation 5550
 
9.8%
Dash Punctuation 2775
 
4.9%
Decimal Number 2775
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
т 11280
24.7%
а 5816
12.7%
м 5640
12.3%
о 3004
 
6.6%
в 2908
 
6.4%
и 2818
 
6.2%
х 2818
 
6.2%
у 2785
 
6.1%
п 2785
 
6.1%
с 2775
 
6.1%
Other values (8) 3086
 
6.8%
Decimal Number
ValueCountFrequency (%)
5 1985
71.5%
6 747
 
26.9%
4 43
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 5550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2775
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 45715
80.5%
Common 11100
 
19.5%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
т 11280
24.7%
а 5816
12.7%
м 5640
12.3%
о 3004
 
6.6%
в 2908
 
6.4%
и 2818
 
6.2%
х 2818
 
6.2%
у 2785
 
6.1%
п 2785
 
6.1%
с 2775
 
6.1%
Other values (8) 3086
 
6.8%
Common
ValueCountFrequency (%)
. 5550
50.0%
- 2775
25.0%
5 1985
 
17.9%
6 747
 
6.7%
4 43
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 45715
80.5%
ASCII 11100
 
19.5%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
т 11280
24.7%
а 5816
12.7%
м 5640
12.3%
о 3004
 
6.6%
в 2908
 
6.4%
и 2818
 
6.2%
х 2818
 
6.2%
у 2785
 
6.1%
п 2785
 
6.1%
с 2775
 
6.1%
Other values (8) 3086
 
6.8%
ASCII
ValueCountFrequency (%)
. 5550
50.0%
- 2775
25.0%
5 1985
 
17.9%
6 747
 
6.7%
4 43
 
0.4%

conditioner
Categorical

MISSING 

Distinct3
Distinct (%)0.1%
Missing1006
Missing (%)16.6%
Memory size780.5 KiB
климатконтроль
3222 
кондиционер
1477 
безкондиционера
356 

Length

Max length15
Median length14
Mean length13.193867
Min length11

Characters and Unicode

Total characters66695
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowклиматконтроль
2nd rowклиматконтроль
3rd rowклиматконтроль
4th rowклиматконтроль
5th rowклиматконтроль

Common Values

ValueCountFrequency (%)
климатконтроль 3222
53.2%
кондиционер 1477
24.4%
безкондиционера 356
 
5.9%
(Missing) 1006
 
16.6%

Length

2025-02-27T20:21:33.103863image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-27T20:21:33.420918image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
климатконтроль 3222
63.7%
кондиционер 1477
29.2%
безкондиционера 356
 
7.0%

Most occurring characters

ValueCountFrequency (%)
о 10110
15.2%
к 8277
12.4%
и 6888
10.3%
н 6888
10.3%
л 6444
9.7%
т 6444
9.7%
р 5055
7.6%
а 3578
 
5.4%
м 3222
 
4.8%
ь 3222
 
4.8%
Other values (5) 6567
9.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 66695
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 10110
15.2%
к 8277
12.4%
и 6888
10.3%
н 6888
10.3%
л 6444
9.7%
т 6444
9.7%
р 5055
7.6%
а 3578
 
5.4%
м 3222
 
4.8%
ь 3222
 
4.8%
Other values (5) 6567
9.8%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 66695
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 10110
15.2%
к 8277
12.4%
и 6888
10.3%
н 6888
10.3%
л 6444
9.7%
т 6444
9.7%
р 5055
7.6%
а 3578
 
5.4%
м 3222
 
4.8%
ь 3222
 
4.8%
Other values (5) 6567
9.8%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 66695
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 10110
15.2%
к 8277
12.4%
и 6888
10.3%
н 6888
10.3%
л 6444
9.7%
т 6444
9.7%
р 5055
7.6%
а 3578
 
5.4%
м 3222
 
4.8%
ь 3222
 
4.8%
Other values (5) 6567
9.8%

audio
Categorical

MISSING 

Distinct4
Distinct (%)0.1%
Missing1575
Missing (%)26.0%
Memory size934.3 KiB
автомагнитолаCD/MP3(сUSBиBluetooth)
2340 
автомагнитола
1002 
автомагнитолаCD/MP3(безUSB)
819 
автомагнитолаHi-End
325 

Length

Max length35
Median length35
Mean length27.46634
Min length13

Characters and Unicode

Total characters123214
Distinct characters36
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowавтомагнитолаCD/MP3(сUSBиBluetooth)
2nd rowавтомагнитолаCD/MP3(безUSB)
3rd rowавтомагнитолаCD/MP3(сUSBиBluetooth)
4th rowавтомагнитолаCD/MP3(безUSB)
5th rowавтомагнитолаCD/MP3(безUSB)

Common Values

ValueCountFrequency (%)
автомагнитолаCD/MP3(сUSBиBluetooth) 2340
38.6%
автомагнитола 1002
16.5%
автомагнитолаCD/MP3(безUSB) 819
 
13.5%
автомагнитолаHi-End 325
 
5.4%
(Missing) 1575
26.0%

Length

2025-02-27T20:21:33.533944image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-27T20:21:33.648970image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
автомагнитолаcd/mp3(сusbиbluetooth 2340
52.2%
автомагнитола 1002
22.3%
автомагнитолаcd/mp3(безusb 819
 
18.3%
автомагнитолаhi-end 325
 
7.2%

Most occurring characters

ValueCountFrequency (%)
а 13458
 
10.9%
т 8972
 
7.3%
о 8972
 
7.3%
и 6826
 
5.5%
B 5499
 
4.5%
o 4680
 
3.8%
t 4680
 
3.8%
м 4486
 
3.6%
г 4486
 
3.6%
н 4486
 
3.6%
Other values (26) 56669
46.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 85150
69.1%
Uppercase Letter 25103
 
20.4%
Open Punctuation 3159
 
2.6%
Close Punctuation 3159
 
2.6%
Other Punctuation 3159
 
2.6%
Decimal Number 3159
 
2.6%
Dash Punctuation 325
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
а 13458
15.8%
т 8972
10.5%
о 8972
10.5%
и 6826
 
8.0%
o 4680
 
5.5%
t 4680
 
5.5%
м 4486
 
5.3%
г 4486
 
5.3%
н 4486
 
5.3%
л 4486
 
5.3%
Other values (12) 19618
23.0%
Uppercase Letter
ValueCountFrequency (%)
B 5499
21.9%
U 3159
12.6%
S 3159
12.6%
C 3159
12.6%
P 3159
12.6%
M 3159
12.6%
D 3159
12.6%
H 325
 
1.3%
E 325
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 3159
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3159
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3159
100.0%
Decimal Number
ValueCountFrequency (%)
3 3159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 325
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 65455
53.1%
Latin 44798
36.4%
Common 12961
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 5499
12.3%
o 4680
10.4%
t 4680
10.4%
U 3159
 
7.1%
S 3159
 
7.1%
C 3159
 
7.1%
P 3159
 
7.1%
M 3159
 
7.1%
D 3159
 
7.1%
h 2340
 
5.2%
Other values (8) 8645
19.3%
Cyrillic
ValueCountFrequency (%)
а 13458
20.6%
т 8972
13.7%
о 8972
13.7%
и 6826
10.4%
м 4486
 
6.9%
г 4486
 
6.9%
н 4486
 
6.9%
л 4486
 
6.9%
в 4486
 
6.9%
с 2340
 
3.6%
Other values (3) 2457
 
3.8%
Common
ValueCountFrequency (%)
( 3159
24.4%
) 3159
24.4%
/ 3159
24.4%
3 3159
24.4%
- 325
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 65455
53.1%
ASCII 57759
46.9%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
а 13458
20.6%
т 8972
13.7%
о 8972
13.7%
и 6826
10.4%
м 4486
 
6.9%
г 4486
 
6.9%
н 4486
 
6.9%
л 4486
 
6.9%
в 4486
 
6.9%
с 2340
 
3.6%
Other values (3) 2457
 
3.8%
ASCII
ValueCountFrequency (%)
B 5499
 
9.5%
o 4680
 
8.1%
t 4680
 
8.1%
( 3159
 
5.5%
) 3159
 
5.5%
U 3159
 
5.5%
S 3159
 
5.5%
C 3159
 
5.5%
/ 3159
 
5.5%
P 3159
 
5.5%
Other values (13) 20787
36.0%

mileage
Real number (ℝ)

MISSING 

Distinct688
Distinct (%)14.0%
Missing1145
Missing (%)18.9%
Infinite0
Infinite (%)0.0%
Mean228454.82
Minimum11000
Maximum600000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.7 KiB
2025-02-27T20:21:33.802004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile90000
Q1159000
median221000
Q3290000
95-th percentile400000
Maximum600000
Range589000
Interquartile range (IQR)131000

Descriptive statistics

Standard deviation94972.717
Coefficient of variation (CV)0.41571772
Kurtosis0.71328468
Mean228454.82
Median Absolute Deviation (MAD)67175
Skewness0.5992983
Sum1.1230839 × 109
Variance9.019817 × 109
MonotonicityNot monotonic
2025-02-27T20:21:33.956056image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 253
 
4.2%
200000 191
 
3.2%
250000 134
 
2.2%
270000 86
 
1.4%
280000 83
 
1.4%
240000 81
 
1.3%
230000 80
 
1.3%
170000 80
 
1.3%
400000 77
 
1.3%
150000 76
 
1.3%
Other values (678) 3775
62.3%
(Missing) 1145
 
18.9%
ValueCountFrequency (%)
11000 1
< 0.1%
11500 1
< 0.1%
12340 1
< 0.1%
14000 1
< 0.1%
15000 1
< 0.1%
17000 1
< 0.1%
18000 2
< 0.1%
19000 1
< 0.1%
20000 2
< 0.1%
26000 1
< 0.1%
ValueCountFrequency (%)
600000 13
0.2%
580000 2
 
< 0.1%
570000 2
 
< 0.1%
560000 5
 
0.1%
555500 1
 
< 0.1%
552300 7
0.1%
550000 3
 
< 0.1%
545000 2
 
< 0.1%
544000 2
 
< 0.1%
543000 1
 
< 0.1%

contact
Text

Distinct1190
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size613.4 KiB
2025-02-27T20:21:34.310553image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length82
Median length27
Mean length6.2405544
Min length1

Characters and Unicode

Total characters37824
Distinct characters141
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique771 ?
Unique (%)12.7%

Sample

1st rowToyota
2nd rowCaddy
3rd rowToyota
4th rowРыбница
5th rowРыбница
ValueCountFrequency (%)
usauto 410
 
6.8%
александр 340
 
5.6%
сергей 305
 
5.0%
дмитрий 178
 
2.9%
игорь 172
 
2.8%
олег 172
 
2.8%
андрей 170
 
2.8%
евгений 120
 
2.0%
владимир 117
 
1.9%
вадим 106
 
1.7%
Other values (1076) 3971
65.5%
2025-02-27T20:21:34.828844image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
а 2673
 
7.1%
и 2633
 
7.0%
е 2194
 
5.8%
р 2109
 
5.6%
л 1809
 
4.8%
н 1657
 
4.4%
7 1581
 
4.2%
й 1329
 
3.5%
с 1080
 
2.9%
д 1040
 
2.7%
Other values (131) 19719
52.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26456
69.9%
Uppercase Letter 5807
 
15.4%
Decimal Number 5260
 
13.9%
Other Punctuation 166
 
0.4%
Math Symbol 69
 
0.2%
Dash Punctuation 34
 
0.1%
Close Punctuation 13
 
< 0.1%
Currency Symbol 8
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Other Number 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
а 2673
 
10.1%
и 2633
 
10.0%
е 2194
 
8.3%
р 2109
 
8.0%
л 1809
 
6.8%
н 1657
 
6.3%
й 1329
 
5.0%
с 1080
 
4.1%
д 1040
 
3.9%
т 912
 
3.4%
Other values (48) 9020
34.1%
Uppercase Letter
ValueCountFrequency (%)
А 851
14.7%
В 700
 
12.1%
С 494
 
8.5%
Д 368
 
6.3%
И 360
 
6.2%
A 302
 
5.2%
S 262
 
4.5%
М 240
 
4.1%
U 225
 
3.9%
О 215
 
3.7%
Other values (42) 1790
30.8%
Other Punctuation
ValueCountFrequency (%)
. 122
73.5%
* 18
 
10.8%
, 9
 
5.4%
! 4
 
2.4%
/ 4
 
2.4%
@ 3
 
1.8%
% 2
 
1.2%
; 1
 
0.6%
: 1
 
0.6%
? 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
7 1581
30.1%
0 631
 
12.0%
1 464
 
8.8%
3 423
 
8.0%
8 413
 
7.9%
5 404
 
7.7%
2 376
 
7.1%
9 364
 
6.9%
6 323
 
6.1%
4 281
 
5.3%
Math Symbol
ValueCountFrequency (%)
+ 67
97.1%
= 2
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 31
91.2%
— 3
 
8.8%
Currency Symbol
ValueCountFrequency (%)
₽ 5
62.5%
$ 3
37.5%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Number
ValueCountFrequency (%)
⁰ 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 27030
71.5%
Common 5561
 
14.7%
Latin 5233
 
13.8%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
а 2673
 
9.9%
и 2633
 
9.7%
е 2194
 
8.1%
р 2109
 
7.8%
л 1809
 
6.7%
н 1657
 
6.1%
й 1329
 
4.9%
с 1080
 
4.0%
д 1040
 
3.8%
т 912
 
3.4%
Other values (49) 9594
35.5%
Latin
ValueCountFrequency (%)
u 654
12.5%
o 556
 
10.6%
t 512
 
9.8%
a 472
 
9.0%
A 302
 
5.8%
s 290
 
5.5%
S 262
 
5.0%
U 225
 
4.3%
i 224
 
4.3%
e 208
 
4.0%
Other values (41) 1528
29.2%
Common
ValueCountFrequency (%)
7 1581
28.4%
0 631
 
11.3%
1 464
 
8.3%
3 423
 
7.6%
8 413
 
7.4%
5 404
 
7.3%
2 376
 
6.8%
9 364
 
6.5%
6 323
 
5.8%
4 281
 
5.1%
Other values (21) 301
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 27030
71.5%
ASCII 10782
 
28.5%
Currency Symbols 5
 
< 0.1%
None 4
 
< 0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
а 2673
 
9.9%
и 2633
 
9.7%
е 2194
 
8.1%
р 2109
 
7.8%
л 1809
 
6.7%
н 1657
 
6.1%
й 1329
 
4.9%
с 1080
 
4.0%
д 1040
 
3.8%
т 912
 
3.4%
Other values (49) 9594
35.5%
ASCII
ValueCountFrequency (%)
7 1581
 
14.7%
u 654
 
6.1%
0 631
 
5.9%
o 556
 
5.2%
t 512
 
4.7%
a 472
 
4.4%
1 464
 
4.3%
3 423
 
3.9%
8 413
 
3.8%
5 404
 
3.7%
Other values (69) 4672
43.3%
Currency Symbols
ValueCountFrequency (%)
₽ 5
100.0%
None
ValueCountFrequency (%)
⁰ 4
100.0%
Punctuation
ValueCountFrequency (%)
— 3
100.0%

fone
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size431.8 KiB

date_notice
Date

Distinct5940
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size94.7 KiB
Minimum2022-12-05 15:30:00
Maximum2025-01-28 21:32:00
2025-02-27T20:21:34.979890image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:35.136926image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

manth
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size94.7 KiB

model
Text

Distinct562
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
2025-02-27T20:21:35.557487image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length6.4939779
Min length1

Characters and Unicode

Total characters39360
Distinct characters91
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)3.0%

Sample

1st rowAvensis
2nd rowCaddy
3rd rowPrius
4th row5er 520
5th rowGX
ValueCountFrequency (%)
passat 335
 
4.0%
rx 328
 
3.9%
e 232
 
2.8%
e-klasse 228
 
2.7%
avensis 199
 
2.4%
5er 174
 
2.1%
prius 172
 
2.1%
camry 169
 
2.0%
450h 165
 
2.0%
golf 159
 
1.9%
Other values (540) 6172
74.1%
2025-02-27T20:21:36.105112image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3716
 
9.4%
s 2724
 
6.9%
r 2353
 
6.0%
2272
 
5.8%
e 2271
 
5.8%
0 1839
 
4.7%
o 1558
 
4.0%
n 1384
 
3.5%
i 1375
 
3.5%
l 1261
 
3.2%
Other values (81) 18607
47.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22841
58.0%
Uppercase Letter 7624
 
19.4%
Decimal Number 5948
 
15.1%
Space Separator 2272
 
5.8%
Dash Punctuation 633
 
1.6%
Close Punctuation 15
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Other Punctuation 10
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3716
16.3%
s 2724
11.9%
r 2353
10.3%
e 2271
9.9%
o 1558
 
6.8%
n 1384
 
6.1%
i 1375
 
6.0%
l 1261
 
5.5%
t 1137
 
5.0%
u 699
 
3.1%
Other values (30) 4363
19.1%
Uppercase Letter
ValueCountFrequency (%)
C 885
11.6%
A 833
10.9%
P 701
9.2%
S 699
9.2%
X 676
8.9%
E 654
8.6%
R 536
 
7.0%
V 484
 
6.3%
M 390
 
5.1%
G 328
 
4.3%
Other values (22) 1438
18.9%
Decimal Number
ValueCountFrequency (%)
0 1839
30.9%
5 943
15.9%
2 822
13.8%
3 713
 
12.0%
4 509
 
8.6%
1 359
 
6.0%
6 351
 
5.9%
7 195
 
3.3%
8 147
 
2.5%
9 70
 
1.2%
Other Punctuation
ValueCountFrequency (%)
' 4
40.0%
/ 4
40.0%
, 1
 
10.0%
& 1
 
10.0%
Space Separator
ValueCountFrequency (%)
2272
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 633
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30408
77.3%
Common 8895
 
22.6%
Cyrillic 57
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3716
 
12.2%
s 2724
 
9.0%
r 2353
 
7.7%
e 2271
 
7.5%
o 1558
 
5.1%
n 1384
 
4.6%
i 1375
 
4.5%
l 1261
 
4.1%
t 1137
 
3.7%
C 885
 
2.9%
Other values (42) 11744
38.6%
Cyrillic
ValueCountFrequency (%)
а 8
14.0%
С 6
10.5%
Т 6
10.5%
е 4
 
7.0%
я 4
 
7.0%
г 3
 
5.3%
Я 3
 
5.3%
у 3
 
5.3%
р 3
 
5.3%
Д 3
 
5.3%
Other values (10) 14
24.6%
Common
ValueCountFrequency (%)
2272
25.5%
0 1839
20.7%
5 943
10.6%
2 822
 
9.2%
3 713
 
8.0%
- 633
 
7.1%
4 509
 
5.7%
1 359
 
4.0%
6 351
 
3.9%
7 195
 
2.2%
Other values (9) 259
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39303
99.9%
Cyrillic 57
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3716
 
9.5%
s 2724
 
6.9%
r 2353
 
6.0%
2272
 
5.8%
e 2271
 
5.8%
0 1839
 
4.7%
o 1558
 
4.0%
n 1384
 
3.5%
i 1375
 
3.5%
l 1261
 
3.2%
Other values (61) 18550
47.2%
Cyrillic
ValueCountFrequency (%)
а 8
14.0%
С 6
10.5%
Т 6
10.5%
е 4
 
7.0%
я 4
 
7.0%
г 3
 
5.3%
Я 3
 
5.3%
у 3
 
5.3%
р 3
 
5.3%
Д 3
 
5.3%
Other values (10) 14
24.6%

len_dop_info
Real number (ℝ)

Distinct974
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246.99588
Minimum1
Maximum3915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.7 KiB
2025-02-27T20:21:36.255143image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q155
median153
Q3348
95-th percentile793
Maximum3915
Range3914
Interquartile range (IQR)293

Descriptive statistics

Standard deviation275.13
Coefficient of variation (CV)1.1139053
Kurtosis11.806746
Mean246.99588
Median Absolute Deviation (MAD)123
Skewness2.3144398
Sum1497042
Variance75696.52
MonotonicityNot monotonic
2025-02-27T20:21:36.410177image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 759
 
12.5%
76 32
 
0.5%
25 29
 
0.5%
31 29
 
0.5%
26 27
 
0.4%
83 25
 
0.4%
18 23
 
0.4%
67 23
 
0.4%
96 23
 
0.4%
77 22
 
0.4%
Other values (964) 5069
83.6%
ValueCountFrequency (%)
1 1
 
< 0.1%
3 759
12.5%
4 5
 
0.1%
5 4
 
0.1%
6 9
 
0.1%
7 6
 
0.1%
8 4
 
0.1%
9 22
 
0.4%
10 3
 
< 0.1%
11 10
 
0.2%
ValueCountFrequency (%)
3915 1
< 0.1%
3339 1
< 0.1%
2704 1
< 0.1%
2099 1
< 0.1%
1963 1
< 0.1%
1843 1
< 0.1%
1804 1
< 0.1%
1643 1
< 0.1%
1633 1
< 0.1%
1628 1
< 0.1%

mileage_orig
Real number (ℝ)

MISSING 

Distinct676
Distinct (%)21.5%
Missing2919
Missing (%)48.2%
Infinite0
Infinite (%)0.0%
Mean214137.73
Minimum5000
Maximum600000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.7 KiB
2025-02-27T20:21:36.561212image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile50000
Q1145073.5
median212000
Q3280000
95-th percentile373000
Maximum600000
Range595000
Interquartile range (IQR)134926.5

Descriptive statistics

Standard deviation97466.434
Coefficient of variation (CV)0.4551577
Kurtosis0.045842942
Mean214137.73
Median Absolute Deviation (MAD)68000
Skewness0.18373193
Sum6.7282073 × 108
Variance9.4997057 × 109
MonotonicityNot monotonic
2025-02-27T20:21:36.709336image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 144
 
2.4%
200000 110
 
1.8%
250000 76
 
1.3%
270000 48
 
0.8%
240000 46
 
0.8%
280000 46
 
0.8%
230000 46
 
0.8%
180000 45
 
0.7%
220000 45
 
0.7%
290000 44
 
0.7%
Other values (666) 2492
41.1%
(Missing) 2919
48.2%
ValueCountFrequency (%)
5000 1
 
< 0.1%
5555 1
 
< 0.1%
6000 1
 
< 0.1%
6500 1
 
< 0.1%
7000 2
 
< 0.1%
8000 1
 
< 0.1%
10000 8
0.1%
10200 1
 
< 0.1%
10800 1
 
< 0.1%
11000 1
 
< 0.1%
ValueCountFrequency (%)
600000 2
 
< 0.1%
580000 1
 
< 0.1%
560000 1
 
< 0.1%
552300 7
0.1%
526000 1
 
< 0.1%
511000 1
 
< 0.1%
500000 2
 
< 0.1%
490000 1
 
< 0.1%
480000 1
 
< 0.1%
470000 2
 
< 0.1%

Interactions

2025-02-27T20:21:28.628852image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.125927image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.801176image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.457196image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.118384image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.779613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:28.739984image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.245054image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.909201image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.564223image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.230473image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.894651image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:28.843991image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.355076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.017225image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.672270image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.335510image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:28.166802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:28.954017image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.461099image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.123247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.783293image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.441518image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:28.275824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:29.067149image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.574138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.232274image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.892324image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.550558image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:28.390850image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:29.188162image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:25.690165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:26.350174image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.007359image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:27.669605image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-27T20:21:28.513824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Missing values

2025-02-27T20:21:29.367216image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-27T20:21:29.683779image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-27T20:21:29.922473image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

brendvolumetip_dvigateljagodprisebodystatedoorfueltransmissionconditioneraudiomileagecontactfonedate_noticemanthmodellen_dop_infomileage_orig
0Toyota2000.00Дизель20095900.00универсалОтличное4/5дизель6-тиступ.мех.климатконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)212000.00Toyota779104072025-01-28 21:32:002025-01Avensis334212000.00
1Volkswagen2000.00Бензин-Газ20076200.00минивенОтличное4/5бензин5-тиступ.мех.климатконтрольавтомагнитолаCD/MP3(безUSB)190000.00Caddy777427942025-01-28 21:23:002025-01Caddy3NaN
2Toyota1800.00Гибрид20098999.00хетчбекОтличное4/5бензинавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)157000.00Toyota779895662025-01-28 21:23:002025-01Prius3157000.00
3BMW2000.00Бензин19971700.00NaNХорошееNaNNaN5-тиступ.мех.климатконтрольавтомагнитолаCD/MP3(безUSB)NaNРыбница778005862025-01-28 21:07:002025-015er 52064NaN
4Lexus4600.00Бензин201229000.00NaNОтличноеNaNNaNавтоматклиматконтрольавтомагнитолаCD/MP3(безUSB)NaNРыбница778005862025-01-28 21:05:002025-01GX354NaN
5Mercedes-Benz3200.00Дизель200810000.00внедорожникХорошее4/5дизельавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)294000.00Владимир774562302025-01-28 20:52:002025-01GL-klasse GL 32018294000.00
6Toyota1800.00Гибрид20137500.00хетчбекОтличное4/5NaNавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)NaNРххх775332042025-01-28 20:45:002025-01Prius72NaN
7Ford2000.00Бензин20156700.00седанОтличное4/5бензинавтоматкондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)140000.00Юрий777920302025-01-28 20:42:002025-01Focus165NaN
8Volkswagen1400.00Бензин-Газ20118100.00универсалОтличное4/5бензинавтоматклиматконтрольавтомагнитолаHi-End261000.00Василий778524322025-01-28 20:42:002025-01Passat258261000.00
9Lexus3500.00Бензин-Газ20099000.00внедорожникОтличное4/5бензинавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)160000.00Владимир774562302025-01-28 20:38:002025-01RX 35015160000.00
brendvolumetip_dvigateljagodprisebodystatedoorfueltransmissionconditioneraudiomileagecontactfonedate_noticemanthmodellen_dop_infomileage_orig
8992VolkswagenNaNБензин20106000.00кроссоверNaNNaNNaNавтоматNaNNaN200000.00геннадий778196482022-12-07 20:00:002022-12Tiguan5NaN
8993Volkswagen1800.00Бензин-Газ19911400.00седанОтличное4/5газ5-тиступ.мех.кондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)123456.00Евгений779988962022-12-07 19:52:002022-12Passat23123456.00
8994Nissan2000.00Бензин19981500.00хетчбекХорошее4/5бензин5-тиступ.мех.кондиционеравтомагнитолаCD/MP3(безUSB)290000.00Иван777970362022-12-07 16:06:002022-12Primera3NaN
8999Toyota1995.00Дизель20053700.00универсалОтличное4/5дизель5-тиступ.мех.климатконтрольавтомагнитола233000.00Виктор779755832022-12-07 09:45:002022-12Corolla161233000.00
9000Toyota2000.00Дизель20012500.00универсалХорошее4/5дизель6-тиступ.мех.NaNNaN271000.00Александр777808022022-12-06 12:11:002022-12Avensis21NaN
9001Toyota2000.00Дизель20042600.00универсалNaN4/5дизель5-тиступ.мех.кондиционерNaNNaNЕвгений777945232022-12-05 20:30:002022-12Corolla162NaN
9002Mercedes-Benz3200.00Дизель20045800.00универсалОтличноеNaNдизельавтоматклиматконтрольNaN293000.00Александр777992322022-12-05 19:45:002022-12E-klasse E 32018293000.00
9003Volkswagen1900.00Дизель20065300.00хетчбекХорошее4/5дизель6-тиступ.мех.кондиционеравтомагнитола175645.00Владимир777610102022-12-05 15:55:002022-12Golf Plus91175645.00
9004Toyota2000.00Дизель20064500.00универсалОтличное4/5дизель6-тиступ.мех.кондиционеравтомагнитола213456.00Владимир777610102022-12-05 15:39:002022-12Avensis109213456.00
9005Toyota2000.00Дизель20055500.00минивенОтличное4/5дизель6-тиступ.мех.климатконтрольавтомагнитола212443.00Владимир777610102022-12-05 15:30:002022-12Avensis Verso140212443.00

Duplicate rows

Most frequently occurring

brendvolumetip_dvigateljagodprisebodystatedoorfueltransmissionconditioneraudiomileagecontactdate_noticemodellen_dop_infomileage_orig# duplicates
1Mitsubishi1700.00Бензин-Газ19941150.00седанУдовлетворительное4/5газ5-тиступ.мех.безкондиционераавтомагнитола552300.00Дмитрий2024-08-10 22:46:00Galant3552300.003
0Audi2000.00Бензин19921600.00седанОтличное4/5бензин5-тиступ.мех.кондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)NaN0775281762023-04-10 14:14:0080456NaN2
2Toyota2000.00Дизель20064500.00NaNХорошее4/5дизель6-тиступ.мех.климатконтрольавтомагнитола300000.00Виталик2023-03-06 20:36:00Avensis543NaN2
3ToyotaNaNГибрид20108500.00хетчбекХорошее4/5бензинроботизированаякондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)185000.00+373778627262023-01-06 17:17:00Prius168NaN2